Motion fieldnotesOpenAI film study
Timing & transitions · Rendered draft

Hard cut from b-roll to a two-shot, then fade two lower thirds in simultaneously under each speaker

Study the source, inspect the editable build, then adapt the treatment to your own content.

01 / OpenAI source 1:16.7–1:19.2 · Silent research excerpt
02 / Remotion draft Original illustrated content · Editable code

What the source does

Ten frames of b-roll (a seated speaker with a microphone at a dark table, crowd behind) then a hard cut at local frame 10 (master 1850) to a bright two-shot: two people standing in front of a cream wall and a curved black stair rail, banner at right. Starting at ~12 both lower thirds fade in at once, one under each person (left at x≈200, right at x≈1066), reaching full opacity by ~20 (master 1860). Each is a white semibold name over a lighter role line, no plate. The shot then holds.

Cut then paired identification: a hard cut lands the two-shot, and two independent lower thirds share one fade so both subjects are named in a single beat.

Phase notes

  1. Frame 0 — B-roll
  2. Frame 10 — Hard cut to two-shot
  3. Frame 12 — Both lower thirds start fading in
  4. Frame 20 — Lower thirds fully on
  5. Frame 45 — Hold

Use this example

  1. Watch the source and draft at normal speed. Compare the order of actions, the held states, and the transition into the result.
  2. Download the project and read its README before changing inputs. The package includes its implementation and declared dependencies.
  3. Replace the sample content through the package's documented input or content builder. Keep source footage in the research comparison.
  4. Render your adaptation and inspect text fit, framing, intermediate states, and entry and exit frames.
A runnable draft is not a fidelity approval.

The source and remake are different assets. The original code-based illustration remains editable; source footage is a research reference. Read the retained findings below before using the choreography.

Recorded limits

  • Visual fidelity is an authored draft judgement from sampled source frames; no independent blind review or native Resolve execution.

Inspect the original verification record ↗